Method of navigating a vehicle and system thereof

ABSTRACT

The disclosed subject matter includes a method and system for navigating an unmanned ground vehicle (UGV), that include:
         generating, based on the scanning output data, a first map comprising a first group of cells and characterized by a first size;   generating, based on the scanning output data, a second map representing an area smaller than that of the first map comprising a second group of cells, which are characterized by a second size being smaller than the first size; wherein each cell in the first group of cells and the second group of cells is classified to a class selected from at least two classes, comprising traversable and non-traversable, wherein the second part at least partly overlaps the first part; navigating the UGV based on data deduced from crossing between cells in the first map and second map.

TECHNICAL FIELD

The presently disclosed subject matter relates to autonomous navigationin general, and more particularly to navigating an unmanned vehicle.

BACKGROUND

In general, an unmanned ground vehicle (UGV), also referred to as anuncrewed vehicle is a mobile machine that travels by integrating sensorydata with computer-based decision making for the purpose of autonomouslydriving the vehicle. The vehicle can in some cases carry passengers,e.g. operators that cannot see the surrounding environment and/ormanoeuvre the vehicle.

Generally, UGVs comprise various sensors for obtaining information onthe surrounding environment, as well as various sub-systems foroperating, controlling and communicating with the vehicle.

One issue related to UGV operation is autonomous navigation. Whennavigating the vehicle, information with respect to obstacles which arelocated within the traversed area is used for determining a route thatavoids obstacles, to enable the vehicle to safely travel through thearea. An obstacle can be any area or object which should be avoided. Forexample, an obstacle can be an object or area which either blocks orendangers the vehicle, e.g. slopes, holes in the ground, waterreservoirs, walls, big rocks, overhead obstacles e.g., bridges, etc.Obstacles can also be any area which is desired to be avoided (e.g.noxious areas, habitat areas which should be avoided for ecological oranimal conservation reasons, human populated areas which should beavoided for safety reasons, etc.)

When planning a path to a destination, the path should avoid obstacles,and possibly also comply with other limitations, for example beefficient, e.g., should not be elongated unnecessarily. Additionally,due to the near-real-time requirements of navigation tasks and thelimited processing power available at the UGV, planning and tracking apath should be efficient in terms of processing time, processing power,data storage and other resources.

GENERAL DESCRIPTION

The disclosure relates to navigating a UGV within an area, in thepresence of obstacles. Known methods include generating a representationof the area, such as a map or any other internal data structure, therepresentation comprising indications of the obstacles and a destinationof the navigation. The map can then be used for planning a path whichleads to the destination while avoiding obstacles. During actualnavigation, steering commands to the UGV can be generated for followingthe path.

An inherent tradeoff exists between resources such as storage, time andprocessing power, required for generating a map and using the map fornavigating a UGV, on the one hand, and the size of the area representedby the map as well as the map resolution, on the other hand. The largerthe area and/or the higher the resolution, the more resources arerequired for generating a map, planning a path based on the map andcontrolling a UGV in accordance with the path. In particular, in thepresence of obstacles, a high resolution map may be required, since theUGV may have to go through narrow passes or otherwise pass close toobstacles. Additionally, the target destination of the UGV may be at asignificant distance away from a current location, such that a maprepresenting a suitably large area may be required. However, thecomputing resources available for a UGV may be limited, and theprocessing time may also be restricted since real time (or near realtime) processing and vehicle control may be required. Thus, it may beimpractical to use a large map which is also of high resolution.

Some examples of the disclosed subject matter relate to the simultaneousgeneration and usage of two or more maps, wherein one map, referred toherein as “the large map”, represents an area to be navigated in at afirst resolution, and another map, referred to herein as “the smallmap”, represents a smaller area than that of the first map, at a secondresolution, the second resolution being greater than the firstresolution. Each map can be represented as, or can comprise a grid, inwhich each cell is classified as being associated with an areacontaining an obstacle (or part thereof) or not containing an obstacle,e.g., as non-traversable or traversable, respectively. It will beappreciated that, according to examples of the presently disclosedsubject matter, if an obstacle takes up even a fraction of a cell, thecell (the entire cell area) is classified as non-traversable. The cellsof the small map represent smaller areas than those of the large map.The small map and the large map can at least partially overlap, whereincorrelation exists, which maps, within the overlapped parts, each cellin the small map, to one or more cells in the large map, and vice versa.

The maps can be created based on information provided by a scanningdevice which scans the areas surrounding the UGV. Thus, each map can becentered around a current location of the UGV. The small map canrepresent areas adjacent to the UGV at high resolution, while the largemap represents the same areas as well as further areas in one or moredirections, at lower resolution. The two maps can be continuouslyupdated as the UGV advances and readings are received from the scanningdevice, which continuously scans the area around the UGV.

The large map can be used for planning a path from a current location toa target destination, while the small map can be used when the UGV istracking the path for providing accurate steering instructions to theUGV.

In accordance with some examples of the disclosure, planning andtracking the path, using either map, can use crossed information, i.e.,information obtained from the other map which relates to obstacles inthe corresponding area of the used map.

As mentioned above, although an obstacle in any one of the maps isindicated as taking up at least one cell, it can be smaller. Forexample, an obstacle in the large map can be significantly smaller thanthe area represented by a cell in the large map, even to a degree thatit can be ignored or overrun. This information can sometimes be obtainedby crossing the information on the obstacle from the large map, withcorresponding information from the small map. For instance, bydetermining the area that an obstacle takes up in the small map, forexample one or more cells, it can be deduced that the total area of theobstacle is significantly smaller than the area represented by a cell ofthe large map, and can in certain cases be treated accordingly.

In another example, using the small map, it may not be known whether anobstacle located at an edge of the small map extends beyond the arearepresented by the small map, and is actually larger than it seems basedon information from the small map. This can be resolved based oninformation obtained from the corresponding area in the large map.

Thus, an aspect of the disclosed subject matter relates to a method ofnavigating an unmanned ground vehicle (UGV), the vehicle comprising ascanning device, the method comprising: scanning an area surrounding theUGV; operating a processor for generating, based on the data provided bythe scanning, a first map and a second map representing a first part anda second part of the area, respectively the first part and the secondpart at least partially overlap, the first map and the second map beingrelative to a location of the UGV; the first map comprises a first groupof cells of a first size and the second map comprises a second group ofcells of a second size, the first size larger than the second size;classifying cells in the first group of cells or the second group ofcells as traversable or non-traversable; crossing betweennon-traversable cells in the first group of cells and correspondingcells in the second group of cells; deducing, from the crossing, dataindicative of whether a size of a non-traversable area includes an areawhich is smaller than the size of the one or more cells from the firstgroup of cells; and navigating the UGV in accordance with data obtainedfrom the crossing.

Another aspect of the disclosed subject matter relates to a method ofnavigating an unmanned ground vehicle (UGV), the vehicle comprising ascanning device and an Inertial Navigation System (INS) beingoperatively connected to a processor, the method comprising: operatingthe scanning device for executing scanning operations, comprisingscanning an area surrounding the UGV, to thereby generate respectivescanning output data; operating the processor for generating, based onthe scanning output data, a first map representing a first part of thearea, the first map being relative to a location of the UGV andcomprising a first group of cells, each of the first group of cellsrepresenting part of the first part of the area and characterized by afirst size being larger than an accumulated drift value of the INS overa predefined distance, wherein each of the first group of cells isclassified to a class selected from at least two classes, comprisingtraversable and non-traversable; operating the processor for generating,based on the scanning output data, a second map representing a secondpart of the area, the second part being smaller than the first part, thesecond map being relative to the location of the UGV and comprising asecond group of cells, each of the second group of cells representing apart of the second part of the area and characterized by a second sizebeing smaller than the first size and wherein each of the second groupof cells is classified to a class selected from at least two classes,comprising traversable and non-traversable, wherein the second part atleast partly overlaps the first part; crossing between one or more cellsfrom the first group of cells that is classified as non-traversable andone or more corresponding cells from the second group of cells;deducing, from the crossing, data indicative of whether a size of anon-traversable area includes an area which is smaller than the size ofthe one or more cells from the first group of cells; receiving INS dataindicative of a current location of the UGV relative to a previouslocation; updating a location of the UGV relative to non-traversablecells based on the first map and the second map; navigating the UGV inaccordance with data obtained from the crossing.

In addition to the above features, the method according to this aspectof the presently disclosed subject matter can optionally comprise one ormore of features (i) to (xvii) listed below, in any technically possiblecombination or permutation:

-   i). Crossing between one or more second cells from the second group    of cells that is classified as non-traversable and one or more    corresponding cells from the first group of cells; and deducing,    from the crossing, data indicative of whether a size of a    non-traversable area includes an area represented by the second cell    is greater than the size of the second cell.-   ii). Navigating the UGV comprises generating or updating a path to a    destination.-   iii). Navigating the UGV comprises determining steering commands for    controlling movement of the UGV within the area.-   iv). Navigating the UGV is performed in accordance with at least the    second map and the data obtained from the crossing.-   v). Wherein INS data is received repeatedly.-   vi). Comprising navigating the UGV in accordance with at least the    second map and the information.-   vii). Wherein the first map or the second map is generated by    accumulating scanning output data in an advancement direction of the    UGV as the UGV advances into the area, and omitting representation    of areas in an opposite direction beyond a scanning range.-   viii). Repeatedly obtaining a path to a destination of the UGV; and    -   updating the path using the large map and the small map.-   ix). Determining the path to the destination, the path determined so    as to avoid non-traversable cells.-   x). Determining the path to the destination, the path determined so    as to avoid dangerous slopes.-   xi). Receiving a current location of the UGV and a destination    location in absolute coordinates; and    -   determining the path based on the current location and the        destination location.-   xii). Identifying the destination location based on a predetermined    mark, and wherein the path is determined from a current location to    the destination location.-   xiii). Displaying a representation of the map including    non-traversable cells, an indication of a location of the UGV, and    the path.-   xiv). Wherein the predefined distance is selected to exceed a    maximal distance expected to be travelled by the UGV between    consecutive map updates.-   xv). Wherein the predefined distance is equal to a dimension of the    area represented by the first map.-   xvi). Wherein the predefined distance is equal to part (for example    half) a dimension of the area represented by the first map.-   xvii). Wherein the updating is performed for each INS data received.

According to another aspect of the presently disclosed subject matterthere is provided a system mountable on an unmanned ground vehicle(UGV), comprising: a scanning device for scanning an area surroundingthe UGV, to thereby provide scanning output data providing informationon distances between objects in the area and the UGV in a multiplicityof directions; an INS for providing data indicative of a currentlocation of the UGV relative to a previous location; a processorconfigured to: operate the scanning device for executing scanningoperations, comprising scanning an area surrounding the UGV, to therebygenerate respective scanning output data; generate, based on thescanning output data, a first map representing a first part of the area,the first map being relative to a location of the UGV and comprising afirst group of cells, each of the first group of cells representing partof the first part of the area and characterized by a first size beinglarger than an accumulated drift value of the INS over a predefineddistance, wherein each of the first group of cells is classified to aclass selected from at least two classes, comprising traversable andnon-traversable; generate, based on the scanning output data, a secondmap representing a second part of the area, the second part beingsmaller than the first part, the second map being relative to thelocation of the UGV and comprising a second group of cells, each of thesecond cells representing a part of the second part of the area andcharacterized by a second size being smaller than the first size andwherein each of the second group of cells is classified to a classselected from at least two classes, comprising traversable andnon-traversable, wherein the second part at least partly overlaps thefirst part cross between one or more cells from the first group of cellsthat is classified as non-traversable and one or more correspondingcells from the second group of cells; deduce, from the crossing, dataindicative of whether a size of a non-traversable area includes an areawhich is smaller than the size of the one or more cells from the firstgroup of cells; receive INS data indicative of a current location of theUGV relative to a previous location; update a location of the UGVrelative to non-traversable cells on the first map and on the secondmap; and navigate the UGV in accordance with data obtained from thecrossing.

According to another aspect of the presently disclosed subject matterthere is provided an unmanned ground vehicle (UGV), comprising: an INSfor providing data indicative of a current location of the UGV relativeto a previous location; a scanning device for scanning an areasurrounding the UGV, the area having at least predefined areadimensions, to thereby provide scanning output data providinginformation on distances between objects in the area and the UGV in amultiplicity of directions; and a processor configured to: operate thescanning device for executing scanning operations, comprising scanningan area surrounding the UGV, to thereby generate respective scanningoutput data; generate, based on the scanning output data, a first maprepresenting a first part of the area, the first map being relative to alocation of the UGV and comprising a first group of cells, each of thefirst group of cells representing part of the first part of the area andcharacterized by a first size being larger than an accumulated driftvalue of the INS over a predefined distance, wherein each of the firstgroup of cells is classified to a class selected from at least twoclasses, comprising traversable and non-traversable; generate, based onthe scanning output data, a second map representing a second part of thearea, the second part being smaller than the first part, the second mapbeing relative to the location of the UGV and comprising a second groupof cells, each of the second group of cells representing a part of thesecond part of the area and characterized by a second size being smallerthan the first size and wherein each of the second group of cells isclassified to a class selected from at least two classes, comprisingtraversable and non-traversable, wherein the second part at least partlyoverlaps the first part cross between one or more cells from the firstgroup of cells that is classified as non-traversable and one or morecorresponding cells from the second group of cells; deduce, from thecrossing, data indicative of whether a size of a non-traversable areaincludes an area which is smaller than the size of the one or more cellsfrom the first group of cells; receive INS data indicative of a currentlocation of the UGV relative to a previous location; update a locationof the UGV relative to non-traversable cells on the first map and on thesecond map; and navigate the UGV in accordance with data obtained fromthe crossing.

According to another aspect of the presently disclosed subject matterthere is provided a computer program product comprising a computerreadable storage medium retaining program instructions, whose programinstructions, when read by a processor, cause the processor to perform amethod comprising: obtaining scanning output data, the scanning outputdata generated by a scanning device associated with a UGV and executingscanning operations, comprising scanning an area surrounding a UGV, tothereby generate the respective scanning output data; operating theprocessor for generating, based on the scanning output data, a first maprepresenting a first part of the area, the first map being relative to alocation of the UGV and comprising a first group of cells, each of thefirst group of cells representing part of the first part of the area andcharacterized by a first size being larger than an accumulated driftvalue of the INS over a predefined distance, wherein each of the firstgroup of cells is classified to a class selected from at least twoclasses, comprising traversable and non-traversable; operating theprocessor for generating, based on the scanning output data, a secondmap representing a second part of the area, the second part beingsmaller than the first part, the second map being relative to thelocation of the UGV and comprising a second group of cells, each of thesecond group of cells representing a part of the second part of the areaand characterized by a second size being smaller than the first size andwherein each of the second group of cells is classified to a classselected from at least two classes, comprising traversable andnon-traversable, wherein the second part at least partly overlaps thefirst part; crossing between one or more cells from the first group ofcells that is classified as non-traversable and one or morecorresponding cells from the second group of cells; deducing, from thecrossing, data indicative of whether a size of a non-traversable areaincludes an area which is smaller than the size of the one or more cellsfrom the first group of cells; receiving INS data indicative of acurrent location of the UGV relative to a previous location; updating alocation of the UGV relative to non-traversable cells on the first mapand on the second map; and navigating the UGV in accordance with dataobtained from the crossing.

The system, the UGV and the computer program product disclosed inaccordance with the aspects of the presently disclosed subject matterdetailed above can optionally comprise one or more of features (i) to(xvii) listed above, mutatis mutandis, in any technically possiblecombination or permutation.

Another aspect of the disclosed subject matter relates to a method ofnavigating an unmanned ground vehicle (UGV), the vehicle comprising ascanning device being operatively connected to a processor, the methodcomprising: operating the scanning device for executing scanningoperations, comprising scanning an area surrounding the UGV, to therebygenerate respective scanning output data; operating the processor forgenerating, based on the scanning output data, a first map representinga first part of the area, the first map being relative to a location ofthe UGV and comprising a first group of cells, each of the first groupof cells representing part of the first part of the area, wherein eachof the first group of cells is classified to a class selected from atleast two classes, comprising traversable and non-traversable; operatingthe processor for generating, based on the scanning output data, asecond map representing a second part of the area, the second part beingsmaller than the first part, the second map being relative to thelocation of the UGV and comprising a second group of cells, each of thesecond group of cells representing a part of the second part of the areaand characterized by a second size being smaller than the first size andwherein each of the second group of cells is classified to a classselected from at least two classes, comprising traversable andnon-traversable, wherein the second part at least partly overlaps thefirst part crossing between one or more cells from the first group ofcells that is classified as non-traversable and one or morecorresponding cell from the second group of cells; deducing from thecrossing, data indicative of whether a size of a non-traversable areaincludes an area which is smaller than the size of the one or more cellsfrom the first group of cells; updating a location of the UGV relativeto non-traversable cells based on the first map and the second map; andnavigating the UGV in accordance with data obtained from the crossing.

According to another aspect of the presently disclosed subject matterthere is provided a system mountable on an unmanned ground vehicle(UGV), comprising: a scanning device for scanning an area surroundingthe UGV, to thereby provide scanning output data providing informationon distances between objects in the area and the UGV in a multiplicityof directions; a processor configured to operate the scanning device forexecuting scanning operations, comprising scanning an area surroundingthe UGV, to thereby generate respective scanning output data; generate,based on the scanning output data, a first map representing a first partof the area, the first map being relative to a location of the UGV andcomprising a first group of cells, each of the first group of cellsrepresenting part of the first part of the area, wherein each of thefirst group of cells is classified to a class selected from at least twoclasses, comprising traversable and non-traversable; generate, based onthe scanning output data, a second map representing a second part of thearea, the second part being smaller than the first part, the second mapbeing relative to the location of the UGV and comprising a second groupof cells, each of the second cells representing a part of the secondpart of the area and characterized by a second size being smaller thanthe first size and wherein each of the second group of cells isclassified to a class selected from at least two classes, comprisingtraversable and non-traversable, wherein the second part at least partlyoverlaps the first part;

-   -   crossing between one or more cells from the first group of cells        that is classified as non-traversable and one or more        corresponding cells from the second group of cells; deducing,        from the crossing, data indicative of whether a size of a        non-traversable area includes an area which is smaller than the        size of the one or more cells from the first group of cells;        updating a location of the UGV relative to non-traversable cells        on the first map and on the second map; and navigating the UGV        in accordance with data obtained from the crossing.

According to another aspect of the presently disclosed subject matterthere is provided an unmanned ground vehicle (UGV), comprising: ascanning device for scanning an area surrounding the UGV, the areahaving at least predefined area dimensions, to thereby provide scanningoutput data providing information on distances between objects in thearea and the UGV in a multiplicity of directions; and a processorconfigured to operate the scanning device for executing scanningoperations, comprising scanning an area surrounding the UGV, to therebygenerate respective scanning output data; generate, based on thescanning output data, a first map representing a first part of the area,the first map being relative to a location of the UGV and comprising afirst group of cells, each of the first group of cells representing partof the first part of the area and characterized by a first size beinglarger than an accumulated drift value of the INS over a predefineddistance, wherein each of the first group of cells is classified to aclass selected from at least two classes, comprising traversable andnon-traversable; generate, based on the scanning output data, a secondmap representing a second part of the area, the second part beingsmaller than the first part, the second map being relative to thelocation of the UGV and comprising a second group of cells, each of thesecond group of cells representing a part of the second part of the areaand characterized by a second size being smaller than the first size andwherein each of the second group of cells is classified to a classselected from at least two classes, comprising traversable andnon-traversable, wherein the second part at least partly overlaps thefirst part cross between one or more cells from the first group of cellsthat is classified as non-traversable and one or more correspondingcells from the second group of cells; deduce, from the crossing, dataindicative of whether a size of a non-traversable area includes an areawhich is smaller than the size of the one or more cells from the firstgroup of cells; update a location of the UGV relative to non-traversablecells on the first map and on the second map; and navigate the UGV inaccordance with data obtained from the crossing.

According to another aspect of the presently disclosed subject matterthere is provided a computer program product comprising a computerreadable storage medium retaining program instructions, whose programinstructions, when read by a processor, cause the processor to perform amethod comprising: obtaining scanning output data, the scanning outputdata generated by a scanning device associated with a UGV and executingscanning operations, comprising scanning an area surrounding a UGV, tothereby generate the respective scanning output data; operating theprocessor for generating, based on the scanning output data, a first maprepresenting a first part of the area, the first map being relative to alocation of the UGV and comprising a first group of cells, each of thefirst group of cells representing part of the first part of the area,wherein each of the first group of cells is classified to a classselected from at least two classes, comprising traversable andnon-traversable; operating the processor for generating, based on thescanning output data, a second map representing a second part of thearea, the second part being smaller than the first part, the second mapbeing relative to the location of the UGV and comprising a second groupof cells, each of the second group of cells representing a part of thesecond part of the area and characterized by a second size being smallerthan the first size and wherein each of the second group of cells isclassified to a class selected from at least two classes, comprisingtraversable and non-traversable, wherein the second part at least partlyoverlaps the first part; crossing between one or more cells from thefirst group of cells that is classified as non-traversable and one ormore corresponding cells from the second group of cells; deducing, fromthe crossing, data indicative of whether a size of a non-traversablearea includes an area which is smaller than the size of the one or morecells from the first group of cells; updating a location of the UGVrelative to non-traversable cells on the first map and on the secondmap; and navigating the UGV in accordance with data obtained from thecrossing.

The method, system, UGV and computer program product disclosed inaccordance with the aspects of the presently disclosed subject matterdetailed above can optionally comprise one or more of features (i) to(xvii) listed above, mutatis mutandis, in any technically possiblecombination or permutation.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to understand the invention and to see how it can be carriedout in practice, embodiments will be described, by way of non-limitingexamples, with reference to the accompanying drawings, in which:

FIG. 1 illustrates a schematic block diagram of a navigation system of aUGV, in accordance with certain examples of the presently disclosedsubject matter;

FIG. 2 shows a schematic illustration exemplifying an environment inwhich a UGV has to navigate;

FIG. 3 illustrates a generalized flow-chart of a method for navigating aUGV in the presence of obstacles using two maps, in accordance withcertain examples of the presently disclosed subject matter;

FIG. 4 illustrates visual representations of two maps of an environment,in accordance with certain examples of the presently disclosed subjectmatter;

FIG. 5 illustrates a schematic block diagram of a navigation system of aUGV using two maps and an INS, in accordance with certain examples ofthe presently disclosed subject matter; and

FIG. 6 illustrates a generalized flow-chart of a method for navigating aUGV in the presence of obstacles using two maps and an INS, inaccordance with certain examples of the presently disclosed subjectmatter.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are setforth in order to provide a thorough understanding of the invention.However, it will be understood by those skilled in the art that thepresently disclosed subject matter may be practiced without thesespecific details. In other instances, well-known methods, procedures,components and circuits have not been described in detail so as not toobscure the presently disclosed subject matter.

Unless specifically stated otherwise, as apparent from the followingdiscussions, it is appreciated that throughout the specificationdiscussions utilizing terms such as “processing”, “computing”,“determining”, “representing”, “comparing”, “generating”, “assessing”,“matching”, “updating”, “creating” or the like, refer to the action(s)and/or process(es) of a computer that manipulate and/or transform datainto other data, said data represented as physical, such as electronic,quantities and/or said data representing the physical objects.

The terms “processor”, “computer”, “processing unit” or the like shouldbe expansively construed to include any kind of electronic device withdata processing circuitry, which includes a computer processor asdisclosed herein below (e.g., a Central Processing Unit (CPU), amicroprocessor, an electronic circuit, an Integrated Circuit (IC),firmware written for or ported to a specific processor such as digitalsignal processor (DSP), a microcontroller, a field programmable gatearray (FPGA), an application specific integrated circuit (ASIC), etc.)and possibly a computer memory and is capable of executing various dataprocessing operations.

The operations in accordance with the teachings herein may be performedby a computer specially constructed for the desired purposes or by ageneral-purpose computer specially configured for the desired purpose bya computer program stored in a computer readable storage medium.

In the following detailed description, numerous specific details are setforth in order to provide a thorough understanding of the invention.However, it will be understood by those skilled in the art that thepresently disclosed subject matter can be practiced without thesespecific details. In other instances, well-known methods, procedures,components and circuits have not been described in detail so as not toobscure the presently disclosed subject matter.

FIGS. 3 and 6 are flowcharts illustrating operations of respectiveprocesses, in accordance with the presently disclosed subject matter. Inembodiments of the presently disclosed subject matter, fewer, moreand/or different stages than those shown in FIGS. 3 and 6 may beexecuted. In embodiments of the presently disclosed subject matter oneor more stages illustrated in FIGS. 3 and 6 may be executed in adifferent order and/or one or more groups of stages may be executedsimultaneously. For example, block 306 in FIG. 3 can be executedtogether or following the execution of block 308.

FIGS. 1 and 5 illustrate a general schematic of the system architecturein accordance with an example of the presently disclosed subject matter.Each module in FIGS. 1 and 5 can be made up of any combination ofsoftware, hardware and/or firmware that performs the functions asdefined and explained herein. The modules in FIGS. 1 and 5 may becentralized in one location or dispersed over more than one location. Indifferent examples of the presently disclosed subject matter, the systemmay comprise fewer, more, and/or different modules than those shown inFIGS. 1 and 5 .

The term “unmanned ground vehicle” (UGV) as used herein should beexpansively construed to include any kind of a vehicle that can beoperated either autonomously, by a tele-operator, or by an on-boarddriver who cannot see the environment and steers the vehicle e.g. inaccordance with a map or with explicit steering instructions. A UGV inaccordance with the description is equipped with a scanning deviceconfigured to scan the area surrounding the UGV, and an INS configuredto provide positioning data of the UGV.

The term “scanning device” as used herein should be expansivelyconstrued to include any kind of device configured to identify that anobject is present at a specific distance and at a specific directionrelative to the device. Examples of scanning devices include, but arenot limited to: laser scanners (including LIDAR), RADAR, images sensor,sonar, etc. A scanning device can scan for example, 360° on a planesurrounding the device, or in some other smaller scanning angle (e.g.180°). Alternatively, the scanning device can scan a sphere or partthereof around the UGV. A scanning device can provide information forgenerating a 3-dimensional map of the scanned area. In some examples, inorder to save resources, a 2.5-dimensional map can be generated, asdetailed below.

The term “map” as used herein should be expansively construed to includeany data structure representing a geographical area. A map can beabsolute, i.e., comprise indications of absolute coordinates of anobject or a location, or relative, i.e., comprise information onlocations or objects, regardless of their locations in absolutecoordinates. A map can be represented on a computerized display device,on paper, or on any other tangible medium. In some examples of thedisclosure, a 2.5-dimensional map can be generated and used. A2.5-dimensional map relates to a map which indicates the lowest heightof an obstacle above the ground, i.e., the vertical distance between theground and the obstacle at each ground location. In other words, thereis provided, for each ground location, the height of the free spaceabove the ground. Thus, the information indicates, for each location,the clearance height for a UGV, for example the lowest height of atreetop or a bridge at a certain point. It will be appreciated that forobstacles that are on the ground, such as a house or a trunk of a tree,this height can be indicated as zero. The clearance height can be takeninto account for path planning purposes, when determining, for example,whether the UGV can pass under a tree or a bridge.

Reference is now made to FIG. 1 , showing a schematic block diagram of anavigation system of a UGV, in accordance with some examples of thedisclosure.

UGV 100 comprises navigation system 102. It will be appreciated thatnavigation system 102 can comprise components, some of which can alsoserve other purposes, and that components of navigation system 102 canbe located at different parts of UGV 100. Further, navigation system 102can also receive services from and communicate with other components ofUGV 100.

Navigation system 102 can comprise or be otherwise operatively connectedto a scanning device 104 configured to scan an area surrounding thevehicle, and provide scanning output data for generating maps, asfurther described below.

Navigation system 102 can further comprise or be otherwise operativelyconnected to vehicle control sub-systems 112 including for examplesteering control unit, gear control unit, throttle control unit, etc.Vehicle control sub-systems 112 are configured to receive vehiclecontrol instructions (e.g., steering commands) and control UGV 100accordingly. The instructions can be absolute or relative, for examplean absolute instruction can be “go 20 m north”, while a relativeinstruction can be “continue straight for 20 m” or “gas 30%, yaw rate50%”.

Navigation system 102 can further comprise destination obtaining unit116 for obtaining a destination to which UGV 100 has to arrive.Destination obtaining unit 116 can comprise or utilize components suchas but not limited to a Global Positioning System (GPS), a communicationunit for receiving a location or instructions from an external source, acamera and a computerized vision system for capturing images of theenvironment and identifying in the images a predetermined signindicating a target destination. The indication can include for examplevisible or invisible light, a predetermined gesture performed by aperson or a machine, or the like.

UGV 100 can further comprise computer storage device 120 for storinginformation such as one or more maps, information on obstacles,navigation instructions, or the like.

Navigation system 102 can further comprise or be otherwise operativelyconnected to one or more processing units for controlling and executingvarious operations, as disclosed herein. Each processing unit comprisesa respective processing circuitry comprising at least one computerprocessor which can be, for example, operatively connected to acomputer-readable storage device having computer instructions storedthereon to be executed by the computer processor.

According to one example, different functional elements (units, modules)in navigation system 102 can be implemented as a dedicated processingunit comprising a dedicated computer processor and computer storage forexecuting specific operations.

Additionally or alternatively, one or more functional elements can beoperatively connected to a common processing unit configured to executeoperations according to instructions stored in the functional elements.

For example, navigation system 102 can comprise a computer or processingunit (e.g. processor 124), which can be configured to execute severalfunctional modules in accordance with computer-readable instructionsstored on a non-transitory computer-readable medium (e.g. storage device120) operatively connected to processor 124. For illustrative purposessuch functional modules are referred to hereinafter as comprised in theprocessor.

Processor 124 can comprise by way of example, path generation orupdating module 128, maps generation and updating module 132, andsteering commands generation module 136.

Maps generation or updating module 132 can be configured for receivingreadings from scanning device 104 and creating or updating at least alarge map and a small map representing large and small areas,respectively, and comprising cells representing large and small parts ofthe areas, respectively.

In some examples, since scanning device 104 scans around UGV 100, themaps can represent UGV 100 at their centre, and represent obstacles inlocations relative to UGV 100. As part of the maps creation or updating,information related to one or more obstacles can be crossed, and theobstacles, or the cells containing the obstacles in either map, can beclassified accordingly, as detailed below.

Path generation or updating module 128 can be configured to determine apath from a current location of UGV 100 to the obtained destination,wherein the path avoids obstacles. According to one example, the pathplanning is generally based on the large map, but can use information onthe obstacles obtained by crossing information from the two maps, asdetailed below.

Steering commands generation module 126 can be configured to generatesteering commands for controlling UGV 100. Steering command can begenerated for example for following the planned path, based on the pathand on a current location of UGV 100. For example, if UGV 100 gets tooclose to an obstacle, steering commands can be generated so as to keepUGV 100 at a safe distance from the obstacle. UGV 100 advances inaccordance with the steering commands within the area adjacent to UGV100. Accordingly, in some examples, the commands are generated inaccordance with both maps, wherein the instruction generation includescrossing information between the maps, as detailed below.

Referring now to FIG. 2 , this shows a schematic illustration of anexample of an environment in which UGV 200 has to navigate from acurrent location to target location 212. The environment may compriseobstacles such as positive obstacle 204, which is above ground level,negative obstacle 208 which is below ground level, overhead obstacle 205such as a tree or a bridge, steep terrain 206 which may be for example aback, side or front slope. All these obstacles are non-traversable forUGV 200 and have to be avoided. It will be appreciated that some objectspresent an obstacle when accessed from one side, but not when accessedfrom another side. For example, a ramp may present an obstacle whenaccessed from the side, but not when accessed from the front or back.

Traditional methods for navigating within an area in the presence ofobstacles include generating a map of the area comprising indications ofobstacles and optionally a target location or destination and using themap for planning and tracking a path. Although using a high resolutionmap of an area as large as possible (e.g., largest area for whichinformation is available) can serve the two purposes, creating such amap is costly in terms of time and computer resources. Due to theselimitations, these types of maps cannot be created and updated as oftenas required while the UGV advances. Moreover, planning a path based onsuch maps can also require intensive computations, due to the largeamount of data.

Thus, some examples of the disclosure include generating a small map anda large map, and crossing information related to obstacles between thetwo maps.

Generating and using two maps provides for executing the requiredoperations while benefiting from the advantages of a high resolution mapin spite of limited computer processing resources, including, forexample, time, storage space and processing power. Thus, in someexamples larger scale operations including planning a path can beperformed using a large area low-resolution map, while local operations,such as generating steering commands (including commands directed foravoiding obstacles), are done using a smaller high resolution map.Operations can be executed using information crossing between the twomaps.

Referring now to FIG. 3 , this shows a method for navigation within anarea. Operations are described below with reference to elements in FIG.1 , however this is done by way of example only and should not beconstrued as limiting.

At block 300, information including data characterizing the area to betraversed as well as the operational parameters of UGV 100 andnavigation system 102 are received. For example, processor 124 canreceive (300) such information at the onset of vehicle navigation. Thedata can include, but is not limited to, the size or location of thearea to be traversed, obstacle density, UGV maximal or average velocitywithin the terrain, scanning distance, scanning angle (360° or less) andscanning resolution (e.g. every 1⁰, 2⁰, etc.) of one or more scanningdevices comprised by the UGV, maximal or expected velocity of the UGVwithin the area, or the like. Processor 124 can be configured todetermine map parameters of two or more maps, such as the size of thearea represented by each map, map cell size for each map, or the like,as detailed below. It will be appreciated that in some examples the mapsrepresenting the area surrounding the UGV are square. However, in otherexamples the map can be rectangle, or have some other shape.

At block 302 data is repetitively received from a scanning device, suchas scanning device 104 of FIG. 1 . The scanner is operated to scan anarea around the vehicle and generate scanning output data, comprisingone or more readings of distances from the UGV to objects at anydirection. A processor such as processor 124 can receive the scanningdata output. The scanner is operated to provide the readings repeatedly,at a rate depending on the device capabilities, user settings, or thelike. The readings can be received for a full cycle (360⁰) around thedevice, or for a smaller angle, such as 180⁰, 270⁰, or the like. Thereadings can be received at a predefined resolution, such as every 0.5°,every 1⁰, every 2⁰, or the like, horizontally and vertically. It will beappreciated that scanning output data can be received from multiplescanners operatively connected to the UGV, which can be combined forgenerating the maps. It will be appreciated that the height of variousobjects in the area of the UGV can be determined upon the readings invarious vertical directions, thus providing 3-dimensional information.However, in order to save resources, a 2.5-dimensional map can begenerated, updated and used, as detailed above.

At blocks 306 and 308, a large map and a small map, respectively, can begenerated when the first readings are received, and then re-generated orupdated upon receiving subsequent readings. It will be appreciated thatthe maps can alternatively be generated or updated in the reverse orderor simultaneously. The maps can be generated or updated based on thescanning output data, e.g., by processor 124 executing maps generationor updating module 132. It will be appreciated that the maps areinitially generated based upon scanning output data received fromscanner 104, after which the maps can be updated based on furtherscanning output data. According to some examples, each map can begenerated and updated such that it is centred around the UGV and thelocations of obstacles in the area of the UGV are indicated relative tothe UGV. It will be appreciated that the maps generation can alsoutilize additional information, such as existing roads, information onareas that can or cannot be traversed, information obtained from imageanalysis, information indicating whether certain objects are obstaclesor not, or the like, which may be obtained from other sources.

Each map can comprise a grid of cells, wherein each cell represents partof the map area. According to some examples each cell is classified toone of the at least following classes: non-traversable cell (i.e.,representing an area comprising an obstacle or part thereof that shouldthus be avoided); and traversable cell (i.e., representing an area notcomprising an obstacle). In some examples, a cell can also be classifiedas unknown.

It will be appreciated that initially all cells can be classified asunknown. As the UGV gets closer to areas represented by unknown cells,their class can become clear and they can then be classified intotraversable or non-traversable. Otherwise, in some examples, determiningwhether an area represented by a cell with unknown class is traversableor not, can be based on the specific task to be performed, or otherfactors.

A cell is classified in accordance with the readings related tolocations represented by the cell. In some examples, a scanner reading,indicating an obstacle within an area represented by a cell, renders thewhole cell non-traversable. In other examples, a multiplicity of suchreadings can be required in order to render the cell non-traversable,such that false indications resulting from noise are avoided. It will beappreciated that in other examples, further criteria can be applied forclassifying a cell as traversable or non-traversable. However, a cellclassified as traversable ensures that the area represented by the cellis free of obstacles.

In some examples, readings can be received from multiple scanners andintegrated. In such cases, an area can be indicated as non-traversablewith or without regarding the number of scanners that provide readingsrelated to the area represented by the cell.

In some examples, additional information can be associated with one ormore cells on either map, or with obstacles if the internalrepresentation also maintains a collection of obstacles. For example, anon-traversable cell or obstacle can be associated with a sizeindication, for example tiny, small, medium, large and huge, or anyother scale, wherein the size indication can be determined in accordancewith the obstacle area, at least one dimension of the obstacle, or acombination thereof. In a non-limiting example, a tiny object indicationcan be assigned to an object having an area up to the area of one smallcell (i.e. cell of the small map), a small object indication can beassigned to an object having an area up to the area of one large cell(i.e. cell of the large map), a medium object indication can be assignedto an object having an area up to the area of four (2*2 or 1*4) largecells, a large object indication can be assigned to an object having anarea up to the area of (3*3, 4*2 or the like) nine large cells, and ahuge object indication can be assigned to any object taking up an areaof more than nine large cells. It will be appreciated, though, thatother indication schemes can be used, such as small, medium and large.It will be further appreciated that the indications can vary inaccordance with the type of vehicle, the available resolution, theterrain, the task to be performed, or the like.

It will be appreciated that the size indication associated with anobstacle can be determined by the total size of cells indicated asnon-traversable in one or more of the maps. For example, an obstacletaking up at least 3*3 cells in the large map can be considered a hugeobstacle based on the large map only, an obstacle taking up one celllocated on an edge of the small map can be indicated as small, medium,large or even huge if it takes up two or more cells in the large map,depending on the number of cells it takes up in the large map; an objecttaking up one cell in the large map can be indicated as tiny or small ifit takes up one or two cells in the small map, respectively, or thelike. The size can be determined, maintained in association with theobstacle, and re-used when constructing further maps, such that somereal-time calculations can be avoided. Thus, for example, even if asmall portion of an obstacle is shown at an edge of a map, an indicationthat the object is large can be available, and vice versa: an objecttaking up one, two or more cells in the large map can still be tiny orsmall, for example if the obstacle is located on the border of two ormore cells, or on a corner of four cells.

In some examples, obstacles or cells comprising obstacles can also beclassified into types, based on the obstacle shape or on predeterminedknowledge. For example, an obstacle having a small area but significantheight can be classified as a column. Obstacles can also be classifiedbased on whether they are positive, i.e., above ground level, ornegative, i.e. below ground level, such as a ditch.

In some examples, the large map can represent an area of 50-200 metersin each dimension, and each cell can represent an area of about 40-100cm in each dimension.

In some examples, the small map can represent an area of 5-30 meters ineach dimension, and each cell can represent an area of about 10-30 cm ineach dimension.

In some examples, both maps are centred around the UGV, thus the arearepresented by the small map is generally represented by the large mapas well, but with coarser resolution.

Reference is now made also to FIG. 4 , showing a pair of maps 400 and400′ according to one non-limiting example presented for the purpose ofdemonstrating certain principles of the presently disclosed subjectmatter. Map 400 represents an area, sized for example any one of: 5 m*5m, 12 m*12 m, 24 m*24 m or the like, wherein each cell represents anarea of any one of; 0.1*0.1 m, 0.2*0.2 m, or the like. Map 400′represents a larger area, for example any one of: 30 m*30 m, 50 m*50 m,70 m*70 m, or the like, wherein each cell represents an area of any oneof: 0.5*0.5 m, 0.8*0.8 m, or the like.

In the non-limiting example of FIG. 4 , each cell of map 400′ isrepresented as four (2*2) cells in map 400. Thus, map 400 represents asmaller area at finer resolution than map 400′. The area covered by map400 is shown in map 400′ as area 422, as also indicated by the dashedlines.

Maps 400 and 400′ can be created, as described in association withblocks 306 and 308 above, based on readings provided by the scanningdevice, and represent the respective areas at a particular point intime. It will be appreciated that at other points of time, due to newreadings obtained after the UGV has moved, the obstacles can be locatedat different places relative to the UGV. Some obstacles, such as humansor animals, can appear or disappear in subsequent maps.

Maps 400 and 400′ are centred around UGV 404, and show obstacles in therespective areas. The obstacles represented as areas 408, 412, 416, 420,424 and 428 of map 400 are shown also in map 400′ as areas 408′, 412′,416′, 420′, 424′ and 428′, respectively. It will be appreciated thatobstacles are represented as cells, wherein each cell in each map isindicated as either traversable or non-traversable. According to thepresently disclosed subject matter, an “all or nothing” rule isimplemented which defines that an obstacle located within the area of acell renders the entire cell as non-traversable, even if the obstaclecovers only part of the cell area. Thus, even an obstacle that issignificantly smaller than the size of the area represented by a cellwill cause at least one cell to be indicated as non-traversable. Due tothis discretization, the obstacle sizes in maps 400 and 400′ are notnecessarily proportional, and sometimes not even of the same shape. Forexample, a small obstacle that is located within one cell of the smallmap will cause that small cell to be indicated as non-traversable, whilethe same obstacle when located at the corner of four cells and partlyoverlapping four cells of the large map, will cause the four large cellsto be classified as non-traversable. It will be appreciated that theopposite case is also possible, wherein an obstacle is located withinone large cell, but on the corner of four small cells. Even further, ifthe obstacle is located on the border between two small cells (coveringa part of each cell area), the two small cells will be indicated asnon-traversable, resulting in different proportions for the obstacle inthe two maps. For example, an obstacle depicted on the border of twosmall cells will be shaped as a rectangle, while the same obstacle whenlocated within one large cell will be shaped as a square. In anotherexample, as a result of the ‘all or nothing’ rule, an obstacle coveringa single cell 428 in the small map, can also cause a correspondingsingle cell 428′ in the large map to be classified as non-traversable.Crossing information between the two maps will show that the actualobstacle is smaller than the area of a cell in the large map.

Map 400 can be used for planning a path to a destination, whereinobstacles are to be avoided. Commands for steering the UGV can then beprovided based on map 400′, upon the tracked changes in the location ofthe UGV.

Planning the path and generating the commands can include crossinginformation (block 310) between the maps in one or more ways as detailedbelow.

Crossing the information (block 310) can be performed by processor 124during execution of maps generation or updating module 132.Alternatively, operation described with reference to block 310 can beperformed as part of other operations described with reference to otherblocks such as block 318 or block 320, which are detailed below.

Crossing the information between the maps can include associating one ormore obstacles with attributes, based on information from the large mapand the small map.

For example, the size of an obstacle represented by a singlenon-traversable cell in the large map can be determined to be smallerthan the cell size of the large map, if it is represented by one or morecells in the second map that cover an area which is smaller than thearea of the large cell. For example, if the obstacle is represented inthe small map by a single non-traversable cell (overlapping in locationwith the location of the obstacle in the large map) then the obstacle isof size equal or smaller than a small cell. In such cases, the obstaclecan be treated differently, for example ignored or overrun, or thevehicle can possibly run over an area that is part of the large cellwithout hitting the obstacle.

It will be appreciated that comparing the obstacle size between the mapscan also be performed for obstacles taking two blocks of the large maphaving a common edge, wherein the obstacle is located on the border andhas partial overlap with the area represented by each cell. Similarly,an obstacle can be located on a corner common to three or four cells ofthe large map and occupy part of the area represented by each cell.Thus, in this case, an obstacle or a cell in the large map can beclassified as tiny if its size is represented by at most a single cellin the small map, or small if its size is represented by at most asingle cell in the large map. It will be appreciated that furtherattributes can be considered, for example a height of the obstacle e.g.,a box having height of 20 cm can be ignored, while a three-meter polecannot be ignored.

In another example, an obstacle represented as one or morenon-traversable cells located on an edge of the small map, for exampleon the first or last row or column of cells of the small map, can bedetermined to be larger than the obstacle's area, as inferred from thesmall map. Such indication can be deduced from one or morenon-traversable cells of the large map representing areas adjacent tothe relevant small cell(s). Thus, in this example, an obstacle or a cellin the small map can be thus indicated as a large obstacle.

Referring back to FIG. 3 , at block 312, a destination to which the UGVhas to arrive, can be obtained, for example by processor 124. Thedestination can be represented as absolute or relative coordinates. Thedestination can be obtained for example via a communication channel.Alternatively, the destination can be obtained by manually orautomatically searching and identifying a predetermined sign indicatingthe target destination. The predetermined sign can be for example, apointer emitting visible or invisible light, a location in which apredetermined gesture is performed by a person or a machine, or thelike. It will be appreciated that the mentioned options are provided byway of example only and any other method of obtaining a destination canbe used instead. In some examples, the destination can change duringnavigation.

At block 316, a location of the UGV can be obtained, for example from aGlobal Positioning System (GPS) or from another source, for example anInertial Navigation System (INS) associated with the UGV.

At block 318, a path is updated or generated from the current locationto the destination to which the UGV has to arrive, for example by usingthe large map and additional information, including indications obtainedby crossing the large map with the small map, such as indications of asmall obstacle. The path generation or updating can be performed byprocessor 124.

The path can be determined so as to avoid obstacles indicated in themaps by non-traversable cells. The path determination can also take intoaccount dangerous objects as determined from a 2.5-dimensional map, forexample steep or otherwise dangerous slopes. However, path determinationcan also be performed upon a 2-dimensional or 3-dimensional map. Pathdetermination can also take into account objects such as ramps. Rampsmay constitute a traversable slope when accessed from one or moredirections, for example the ascending or descending direction, and anon-traversable obstacle when accessed from the side, a direction fromwhich the ramp may constitute a dangerous slope.

Path generation or updating block 128 can use any path planning methodthat is currently known or will become known in the future. The path caninclude one or more way points. The path determination can take intoaccount additional data characterizing the environment, such as existingroads which are to be used or avoided such that they are not damaged bythe UGV.

The path can be updated in response to new scanning output data receivedfrom the scanning device, in response to update in the destination, orin response to update in the location of the UGV.

At block 320 steering commands are generated for the UGV, in order forthe UGV to track the planned path. The steering commands can begenerated in response to update in the location of the UGV, which can beat a higher frequency than the map updates, for example every 2-50milliseconds. Thus a steering command can be generated each time anindication of a location of the UGV is received, from a GPS system orany other source as disclosed below. Thus, one or more steering commandscan be generated for each map update. During generation of the steeringcommands, the areas adjacent to the UGV can be taken into account, thusthe commands can be determined based on the small map. However,generating the commands can consider the “large obstacle” indicationsthat can be associated with one or more obstacles located on an edge ofthe small map, whose indications are obtained by crossing informationwith the large map.

Vehicle control sub-system can then steer the UGV in accordance with thecommands.

It will be appreciated that the disclosed method can also be used withmore than two maps, wherein each task of the UGV uses a map of theappropriate size and resolution, and information can be crossed betweenany two different maps.

In some examples, the disclosed subject matter can be used fornavigating a UGV using a hybrid approach. In the hybrid approach, a pathof the UGV is generated or updated using a large map of the environmentand information crossed with a small map, as detailed above. Thelocation of the UGV is repeatedly obtained from an Inertial NavigationSystem (INS) implemented as part of navigation system 102, or otherwisemounted on the UGV. INS data can comprise information on a change in theposition, velocity and acceleration of the UGV since a previous reading,thus enabling a processor to determine an updated location of the UGVrelative to the obstacles. Based upon the path and the updated location,steering commands can be generated for advancing the UGV in a safemanner. According to some examples, the commands are generated basedupon the small map, with information crossed with the large map.

The INS provides for avoiding problems of other location-obtainingdevices, such as GPS, which is insufficiently accurate and suffers fromdiscontinuities which can lead to collisions with obstacles or enteringnon-traversable areas. In case readings from the INS are received at ahigher frequency than the readings of the scanning device, the locationof the UGV relative to the obstacles can be updated more often than themap updates. In such cases the steering commands can be generated tobetter adjust the advancement of the UGV within the area. For example,if the INS readings indicate that the UGV is at a distance smaller thana threshold from an obstacle, a steering command that keeps the UGV at asafe distance from the obstacle can be provided.

The cell size of the cells in each map can be selected to be larger thanthe maximal drift that can occur when calculating locations based on theINS during the traversal over some predefined distance (referred toherein as “free-inertial approach”; free inertial navigation approach isalso described in patent application PCT/IL2018/050208 to the Applicantdated Feb. 22, 2018, which is incorporated herein by reference in itsentirety). According to one example, the predefined distance is adistance which is equal to half the edge size of the area depicted bythe associated map (assuming that the UGV is located at the center ofthe map). For example, if the large map represents an area of 70 m by 70m, a deviation of one degree over half the length of the map (35 m)amounts to about 61 cm, (35*tan(1)=0.61). Therefore, if a cell sizelarger than 61 cm is selected for the large map, the presence of anobstacle, even an obstacle smaller than 61 cm, makes one or more cellsof the large map in which at least a part of the object is comprised,into non-traversable. Therefore, since all obstacles are depictedrelatively to the UGV, and wherein each cell of each map is larger thanthe possible drift over half the map size, then even without updatingparts of the map while the UGV advances, which is an assumption that isstricter than the expected situation, the UGV can safely navigatewithout colliding into obstacles notwithstanding the inherent drift ofthe INS.

In some examples, the small map represents an area of 24 m by 24 m,wherein a deviation of one degree over half the length of the map (12 m)amounts to about 61 cm, (35*tan(1)=0.21). Therefore, each cell canrepresent an area of about 21 cm by 21 cm.

In other examples, the cell size can be selected in accordance withother conditions, such as the maximal drift over a full size of the map,or in accordance with other considerations.

Although theoretically, and under the assumption that limitation ofresources such as time and processing power are disregarded, accuratepath planning and navigation can be done using a large map with highresolution. This is not a possibility when using the free-inertialapproach: since the area of each cell in the map is determined based onthe INS drift over a certain distance, the predefined cell size sets alimit on the resolution of the map. Therefore reducing the cell size toincrease the map resolution can be done only if the map size is reducedas well.

Thus, a combination of large and small maps as described above isrequired to remedy the deficiencies of any one map and provide a desiredresolution as well as cover a desired mapped area (e.g., 70 m).

In some examples the maps are constantly updated, such that with everyupdate the UGV remains at the center of each map, while the locations ofobstacles in the area changes relative to the UGV. As the UGV advanceswithin the area, peripheral areas of each map on the sides to which theUGV is advancing get closer to the center, and new areas are mapped andadded to the map, while peripheral areas of the map on the other sidesare not depicted in the updated map, since the covered area no longerincludes them.

Reference is now made to FIG. 5 , showing a navigation system of a UGVusing two maps and an INS, in accordance with some examples of thedisclosure.

Analogously to FIG. 1 above, UGV 500 comprises navigation system 502.Navigation system 502, similarly to navigation system 102 comprisesscanning device 104, vehicle control sub systems 112, destinationobtaining unit 116, storage device 120 and processor 124.

UGV 500 can further comprise inertial measurement unit (IMU) 510providing acceleration data of the UGV, and inertial measurement system514 tracking the position, velocity, and orientation of an object basedon the IMU output data. In some examples, INS 514 comprises IMU 510 toform a self-contained navigation system which uses measurements providedby IMU 510 to track the position, velocity, and orientation of an objectrelative to a starting position, orientation, and velocity.

Processor 124, in addition to path generation/updating module 128 andsteering commands generation module 136 detailed in association withFIG. 1 above, can also comprise updated location calculation module 526for determining the location of the UGV relative to obstacles, based ona previous relative location and the change in the location as receivedfrom INS 514. Relative maps generation/updating module 532 is analogousto maps generation/updating module 132 of FIG. 1 , wherein the maps arecentred around UGV 500 and the obstacles are indicated at locationsrelative to UGV 500.

Reference is now made to FIG. 6 , showing a flowchart of a method fornavigating a UGV using two maps and an INS in the presence of obstacles,in accordance with some examples of the disclosure.

Analogously to FIG. 3 above, at block 30) information including datacharacterizing the area to be traversed as well as the operationalparameters of the UGV 500 and navigation system 502 can be received, forexample by a processor such as processor 124.

At block 302 data scanning output comprising one or more readings ofdistances from the UGV to the closest object at any particular directioncan be received from scanning device 104. Scanning device 104 can beoperated by processor 124, by an internal clock, or by any othercomponent to perform scanning operations. The data is receivedrepeatedly as new readings are provided.

At blocks 606, 608, at least a large relative map and a small relativemap of the area can be generated or updated by relative mapsgeneration/updating module 532, as detailed in association with blocks306, 308 of FIG. 3 above. The maps are relative, such that the UGV islocated at their center, thus the area represented by the small map isincluded in the area represented by the large map.

The size of the area represented by the large map can be determined inaccordance with the range and accuracy of the scanning device. Forexample, a scanning range of 35 m in each direction with accuracyappropriate for the terrain and task, provides for a large maprepresenting a square having an edge of double the scanning distance,i.e., 70 m.

In order for the small map to provide significantly higher resolution,the cell size of the small map can be selected, for example, to be 0.1m*0.1 m, and the small map can cover an area of 14 m*14 m.

In some further examples, the square obtained in accordance with thecalculated edge of either map can be further increased as follows: thescanner generally provides readings around the UGV, therefore acircumcircle can be defined for the square. Then, since round maps maybe inconvenient, a circumgon square can be defined for the circumcircle.The map edge size can then be set to the size of the circumgon edgesize. This amounts to multiplying the obtained distance by the squareroot of two, i.e., about 1.41. The instruction update rate can be set inaccordance with the braking distance of the UGV in the specific terrain.

It will be appreciated, however, that the size of the area representedby either map can be determined in accordance with additional ordifferent parameters, such as the size of the area to be traversed, thescanning range and precision of the scanning device, INS drift,computation capabilities available for the UGV, or other factors.According to some examples the size of the area represented by the largemap is in the order of magnitude of tens of meters, such as 50 m to 200m in each dimension, commands, and the size of the area represented bythe small map is in the order of magnitude of tens of meters, such as 5m to 30 m in each dimension.

At block 310, information can be crossed between the large map and thesmall map, e.g. by one or more of relative maps generation/updatingmodule 532, path generation/updating module 128 or steering commandsgeneration module 136. Crossing the information can comprise associatingadditional information with respect to one or more cells or obstacles.In one example, a small obstacle indication can be associated with anobstacle having overlap with areas represented by up to four cells inthe large map, wherein the indication is determined based on theobstacle size as indicated in the small map. In another example, anobject taking up a single cell on an edge of the small map can beindicated as a larger object if parts thereof are contained in two ormore cells of the large map, in which case it seems as a single-cellobstacle in the small map only due to the relatively small map coveragearea.

The combination of the two maps provides more accurate mapping data ofthe surrounding area that allows the generation of more accuratesteering commands for manoeuvring the vehicle.

At block 312, a destination to arrive at can be obtained, as disclosedin association with FIG. 3 above.

At block 610, one or more readings are received from INS 514 (e.g.received by processor 124), indicating a current location of the UGVrelative to a previous location. The readings can be provided by INS 514at a rate depending on the capabilities of INS 514, user settings, orthe like.

At block 614, the location of areas represented on the map bynon-traversable cells relative to the UGV is updated (e.g. by processor124) in accordance with the INS data. Although the location updaterelates to the UGV, it will be appreciated that updating the location ofthe UGV relative to the cells can be performed by maintaining thelocation of the UGV and updating the relative location of the cells.

In case an obstacle which has been identified in a previous scan is notdetected in the latest scan, due for example to the proximity betweenthe obstacle and the UGV, the obstacle updated location relative to theUGV can still be determined based on its previously determined locationand in accordance with the updated INS data. The relative location canbe used in updating the maps (blocks 606, 608).

At block 316 path to the destination which avoids the obstacles can begenerated or updated, for example by path generation/updating module128. The path can be based upon the large map, with the informationcrossed with the small map. For example, a tiny obstacle can bedisregarded by the path. Generating or updating the path can thus usethe maps, the destination and the updated location of the UGV relativeto the obstacles as determined at block 614.

At block 320 steering command scan be repeatedly generated based on thepath and the updated location, for example by steering commandsgeneration module 136. Steering commands can be generated each time amap is generated or updated, or upon each update in the location of theUGV. The steering commands can be determined in accordance with thesmall map, while taking into account information crossed with the largemap.

A steering module of the UGV can steer the UGV in accordance with theglobal path as updated using vehicle control sub systems 112.

It will be appreciated that any two of the cycles of obtaining thedestination, receiving the scanning device readings and receiving theIMU readings, may, or may not be, synchronized. By way of a non-limitingexample the scanning device readings can be obtained every 10-500milliseconds, e.g., 25 milliseconds, and the IMU readings can beobtained every 2-50 milliseconds, e.g., 20 milliseconds. Steeringcommands can be issued for example at 2-20 Hz.

It is noted that the teachings of the presently disclosed subject matterare not bound by the described with reference to the componentsdescribed on FIG. 1 and FIG. 5 , and to the blocks described on FIG. 3and FIG. 6 . Equivalent and/or modified functionality can beconsolidated or divided in another manner and can be implemented in anyappropriate order or combination of software, firmware and hardware andexecuted on a suitable device.

Those skilled in the art will readily appreciate that variousmodifications and changes can be applied to the examples of theinvention as hereinbefore described without departing from its scope,defined in and by the appended claims.

Examples of the presently disclosed subject matter are not describedwith reference to any particular programming language. It will beappreciated that a variety of programming languages can be used toimplement the teachings of the presently disclosed subject matter asdescribed herein.

The invention claimed is:
 1. A method of autonomous navigation of avehicle using an inertial navigation system (INS), the methodcomprising: operating a scanning device onboard the vehicle forrepeatedly scanning an area surrounding the vehicle, to thereby generaterespective scanning output data; operating a computer processor for:generating, based on the scanning output data a first map representingat least a part of the area and characterized by a first map size;wherein the map comprises a first group of cells characterized by afirst cell size which is equal or larger than an accumulated drift valueof the INS over a first predefined distance which is related to thefirst map size; generating, based on the scanning output, a second maprepresenting a part of the area and characterized by a second map size,which is smaller than the first map size; wherein the map comprises asecond group of cells characterized by a second cell size, smaller thanthe first cell size; wherein the second map, at least partly overlapsthe first map and wherein cells in the first group of cells and thesecond group of cells are classified to a class selected from at leasttwo classes, comprising traversable and non-traversable and whereinnon-traversable cells in the first map and the second map indicateobstacles; generating deduced data by crossing between information aboutone or more cells in the first group of cells and about one or morecells in the second group of cells; wherein the deduced data provides amore accurate indication about size of obstacles located within thearea; receiving INS data from the INS that is indicative of a currentlocation of the vehicle relative to a previous location; and generatingnavigation instructions for leading the vehicle through the area whileavoiding obstacles, based on the INS data the deduced data.
 2. Themethod of claim 1 further comprising executing steering commands forcontrolling movement of the vehicle according to the navigationinstructions.
 3. The method of claim 1, wherein the crossing furthercomprising: crossing between information about one or more cells fromthe first group of cells and information about one or more correspondingcells from the second group of cells, wherein the deduced data isindicative whether a size of a non-traversable area represented by atleast one cell from the first group of cells is smaller than the size ofthe first cell size.
 4. The method of claim 1, wherein the crossingfurther comprising: crossing between one or more cells from the secondgroup of cells that is classified as non-traversable and one or morecorresponding cells from the first group of cells, wherein the deduceddata is indicative whether a size of a non-traversable area representedby at least one cell from the second group is greater than the secondcell size.
 5. The method of claim 1, wherein the second cell size isequal or larger than an accumulated drift value of the INS over a secondpredefined distance, which is related to the second map size of thesecond map.
 6. The method of claim 1, further comprising: updating apath leading the vehicle to a target destination using the first map andthe second map.
 7. The method of claim 1, wherein the first predefineddistance is determined to exceed a maximal distance expected to betravelled by the vehicle between consecutive map updates.
 8. The methodof claim 5, wherein the first predefined distance or the secondpredefined distance is derived from a size of any one of: (i) adimension of an area represented by the first map or the second maprespectively; (ii) half a dimension of an area represented by the firstmap or the second map respectively; and (iii) a diagonal of the firstmap or the second map respectively.
 9. The method of claim 1, whereinthe vehicle is an unmanned ground vehicle.
 10. The method of claim 1,wherein the first map and the second map are generated simultaneously.11. The method of claim 1, wherein the first map or the second map isgenerated by accumulating scanning output data obtained as the vehicleadvances.
 12. A system mountable on a vehicle, comprising: a scanningdevice configured to repeatedly scan an area surrounding the vehicle, tothereby provide scanning output data indicative of distances betweenobjects in the area and the vehicle in a multiplicity of directions; anInertial Navigation System (INS for providing data indicative of acurrent location of the vehicle relative to a previous location; one ormore computer processors configured to: generate, based on the scanningoutput data a first map representing at least a part of the area andcharacterized by a first map size; wherein the map comprises a firstgroup of cells characterized a first cell size which is equal or largerthan an accumulated drift value of the INS over a first predefineddistance which is related to the first map size; generate, based on thescanning output, a second map representing a part of the area andcharacterized by a second map size, which is smaller than the first mapsize; wherein the map comprises a second group of cells characterized bya second cell size, smaller than the first cell size; wherein the secondmap at least partly overlaps the first map and wherein cells in thefirst group of cells and the second group of cells are classified to aclass selected from at least two classes, comprising traversable andnon-traversable and wherein non-traversable cells in the first map andthe second map indicate obstacles; generate deduced data by crossingbetween information about one or more cells in the first group of cellsand about one or more cells in the second group of cells; wherein thededuced data provides a more accurate indication about size of obstacleslocated within the area; receive INS data from the INS that isindicative of a current location of the vehicle relative to a previouslocation; and generate navigation instructions for leading the vehiclethrough the area while avoiding obstacles, based on the INS data and thededuced data.
 13. The system of claim 12 is further configured toexecute steering commands for controlling movement of the vehicleaccording to the navigation instructions.
 14. The system of claim 12,wherein the crossing comprises: crossing between information about oneor more cells from the first group of cells and information about one ormore corresponding cells from the second group of cells, wherein thededuced data is indicative whether a size of a non-traversable arearepresented by at least one cell from the first group of cells issmaller than the first cell size.
 15. The system of claim 12, whereinthe crossing comprises: crossing between one or more cells from thesecond group of cells that is classified as non-traversable and one ormore corresponding cells from the first group of cells, wherein thededuced data is indicative whether a size of a non-traversable arearepresented by at least one cell from the second group is greater thanthe second cell size.
 16. The system of claim 12, wherein the secondcell size is equal or larger than an accumulated drift value of the INSover a second predefined distance, which is related to the second mapsize of the second map.
 17. The system of claim 12 is further configuredto update a path leading the vehicle to a target destination using thefirst map and the second map.
 18. The system of claim 12, wherein thefirst predefined distance is determined to exceed a maximal distanceexpected to be travelled by the vehicle between consecutive map updates.19. The system of claim 16, wherein the first predefined distance or thesecond predefined distance is derived from a size of any one of: (i) adimension of an area represented by the first map or the second maprespectively; (ii) half a dimension of an area represented by the firstmap or the second map respectively; and (iii) a diagonal of the firstmap or the second map respectively.
 20. The system of claim 12 ismountable and operable onboard an unmanned ground vehicle to provide thevehicle with improved obstacle classification and navigationcapabilities.
 21. The system of claim 12, wherein the one or moreprocessors are configured to generate the first map and the second mapsimultaneously.
 22. The system of claim 12, wherein the first map or thesecond map is generated by accumulating scanning output data obtained asthe vehicle advances.
 23. An autonomous vehicle comprising a systemcomprising: a scanning device configured to repeatedly scan an areasurrounding the vehicle, to thereby provide scanning output dataindicative of distances between objects in the area and the vehicle in amultiplicity of directions; an Inertial Navigation System (INS) forproviding data indicative of a current location of the vehicle relativeto a previous location; one or more computer processors configured to:generate, based on the scanning output data a first map representing atleast a part of the area and characterized by a first map size; whereinthe map comprises a first group of cells characterized a first cell sizewhich is equal or larger than an accumulated drift value of the INS overa first predefined distance which is related to the first map size;generate, based on the scanning output, a second map representing a partof the area and characterized by a second map size, which is smallerthan the first map size; wherein the map comprises a second group ofcells characterized by a second cell size, smaller than the first cellsize; wherein the second map at least partly overlaps the first map andwherein cells in the first group of cells and the second group of cellsare classified to a class selected from at least two classes, comprisingtraversable and non-traversable and wherein non-traversable cells in thefirst map and the second map indicate obstacles; generate deduced databy crossing between information about one or more cells in the firstgroup of cells and about one or more cells in the second group of cells;wherein the deduced data provides a more accurate indication about sizeof obstacles located within the area; receive INS data from the INS thatis indicative of a current location of the vehicle relative to aprevious location; and generate navigation instructions for leading thevehicle through the area while avoiding obstacles, based on the INS dataand the deduced data.
 24. A non-transitory program storage devicereadable by a computer, tangibly embodying a program of instructionsexecutable by the computer to perform a method of navigating a vehicleusing an Inertial Navigation System (INS), comprising: obtainingscanning output data generated by a scanning device that is configuredfor repeatedly scanning an area surrounding the vehicle and therebygenerate the scanning output data; generating, based on the scanningoutput data a first map representing at least a part of the area andcharacterized by a first map size; wherein the map comprises a firstgroup of cells characterized a first cell size which is equal or largerthan an accumulated drift value of the INS over a predefined distancewhich is related to the first map size; generating, based on thescanning output, a second map representing a part of the area andcharacterized by a second map size, which is smaller than the first mapsize; wherein the map comprises a second group of cells characterized bya second cell size, smaller than the first cell size; wherein the secondmap at least partly overlaps the first map and wherein cells in thefirst group of cells and the second group of cells are classified to aclass selected from at least two classes, comprising traversable andnon-traversable and wherein non-traversable cells in the first map andthe second map indicate obstacles; generating deduced data by crossingbetween information about one or more cells in the first group of cellsand about one or more cells in the second group of cells; wherein thededuced data provides a more accurate indication about size of obstacleslocated within the area; receiving INS data from the INS that isindicative of a current location of the vehicle relative to a previouslocation; and generating navigation instructions for leading the vehiclethrough the area while avoiding obstacles, based on the INS data and thededuced data.